For the past six months, I’ve warned you about how artificial intelligence will impact the world…

Those who embrace it stand to make a fortune, while those who ignore it could suffer devastating financial hardship.

I’ve shared numerous examples of how AI is changing every aspect of our daily lives and our economy, and how some brilliant people are leveraging AI to create astonishing breakthroughs that were previously thought to be impossible.

Which is why I want to tell you about an announcement from my good friend and colleague Luke Lango.

For the past two years, he’s been spearheading a project to develop one of the most powerful AI-powered stock systems ever created…

And after investing countless hours of training and tweaking, Luke says his project is finally ready to make its public debut.

He calls his new system Prometheus AI, and he’s trained to accomplish one specific task: Detect stocks that jump 100% or more in only four weeks, before it happens.

And tonight at 7:00 p.m. ET, Luke is revealing his powerful new Prometheus AI to the public for the first time ever.

If you want to see this Prometheus AI live in action and learn how you could start using AI to drastically increase your odds of making 100%, 200%, or even 300% in just a handful of weeks…

You should sign up here now.

Because the truth is, an amazing AI-enabled future awaits. This very well may mark the next phase of the AI revolution; there’s no need to overthink it… just get ready for it. As the AI boom ebbs and flows, it will produce continuous waves of investment opportunity.

And I asked Luke Lango to share a few of his thoughts on the matter.

Although Luke lacks artificial intelligence, his Caltech-educated human intelligence is superior to most, as are his informed insights on the latest developments in the world of AI. So please lend an ear to what Luke has to say in the video below.

If you prefer reading to watching, we have also provided a lightly edited transcript of Luke’s comments below.

But before you even click on this video, be sure to sign up for Luke’s Prometheus AI debut tonight at 7:00 p.m. ET.

Click Here to Watch

Hey guys, Luke Lango here.

Now, I’m a Senior Investment Analyst at Investor Place, and Eric Fry has very cordially invited me to give a quick talk to all of you about the state of artificial intelligence these days – or AI.

And that’s because Eric and I are good friends. We go way back. I respect him as a very intelligent, very talented, very capable stock-picker, and like him as a person. And I believe that there’s a two-way street there, a two-way street of respect, and he knows that AI is something that I grew up in and around.

AI is something I have been immersed in for over 10 years now. It’s something that I have been intimately involved with, from developing AI to knowing people who work for AI startups, to knowing people who have founded their own AI companies, that are investing in AI, that are fundraising for AI… The whole AI wheelhouse, that’s my wheelhouse.

A lot of my friends these days work at AI firms, they work at self-driving car companies, they are studying AI at MIT, they’re studying AI at Caltech, at Stanford. They’re doing some very big things in the world of artificial intelligence, and so this is a world that I am intimately familiar with and a world that both Eric and I agree will present some pretty enormous, compelling, and amazing investment opportunities – not just this month, this year, next year, but over the next five to 10 years. This will be an ever-evolving and dynamic landscape of opportunities for investors that know where to look.

So, to sort of help you get prepared for this massive AI investment boom that has already emerged and will continue to emerge, broaden out, and get bigger and stronger over the next several years, Eric has asked me to sort of just do an “AI 101” course here, and to drill down into talking about…

• What exactly is AI? How do people use AI? Where is AI being used today?
• What are the impacts of AI? What are the future impacts going to be?
• What are the implications for the economy, for the stock market?
• What are some good AI stocks to buy?

And so that’s what this video is all about.

Without further ado, let’s get started with the first question, of course, the overarching question: What even is AI, what is artificial intelligence?

Well, artificial intelligence really is just a simulation of human intelligence with machines or computer systems, right? So, there are certain things that require human intelligence in the traditional school of thought – complex reasoning, predictions, rational thought… These are things that require pattern recognition, that require human intelligence.

AI is about simulating those tasks, those things, with machines or computer systems.

Now, how does AI accomplish this?

Well, AI accomplishes this through what’s known as machine-learning algorithms. Machine-learning algorithms are, essentially, a coder will sit down at his computer and write some code and will make it a machine-learning code where the code is set up in a way that it’s a loop. So the machine will loop through the same steps, the same learning algorithm, and then be fed into a bunch of data.

So, you’ll write a piece of code, a machine-learning algorithm, and you’ll feed that into a massive data set – a data set of transportation data, medical data, of biological data, of energy data, of restaurant data, of stock data, of market data, of economic data… whatever data you want.

You create this AI algorithm that’s on a loop. It goes into that data, and it runs the data through the loop and learns from all that data, makes connections from that data, understands where the data is coming from and what it means.

• If X, then Y… if X and Y, then Z…
• If A, B, and C, then D… or, if not A but B, then E…

It is able to make those connections on a level that humans cannot; it’s able to do it instantaneously – much more quickly than a human would ever be able to.

So that’s basically all AI is: Simulation of human intelligence through code that goes into data, learns from that data, and then performs tasks after it has learned from the data.

And another critical component of AI is that it learns from itself. It just gets better and smarter because it’s on that loop, right?

So, I was a college basketball player, and one of my favorite sayings is, Practice, practice, practice makes perfect.

If you want to be a good shooter, get in the gym and shoot. Shoot until your arm falls off. You want to be a good runner, run around the track until your legs fall off. That’s how you get really good at something.

Well, that’s what artificial intelligence is. It’s on a loop and it goes and it goes, and it learns and it learns, and every day new data comes in, right? If you’re talking about an AI algorithm for markets, for trading, every day there’s a whole new deluge of data that can be fed into the system.

It can learn from that data and get better, and so it just goes and goes, and it gets better and smarter. It makes better predictions, more accurate predictions and gets better performing the task it is tasked with completing.

So that’s really all AI is when you break it down, drill down to the bits of it. In its simplest form: It’s code plus data, and that equals artificial intelligence.

Now, another important question here is, well, are there different types of AI? And yes, there are different types of AI.

And the way I like to look at it is there are actually two different types of artificial intelligence…

1. The first type is “narrow” or “specific” AI, as I like to call it.
2. And the second is “general” AI.

The difference is paramount to understanding how to make money from the AI boom because they are very similar in a lot of regards, but different enough that one of them is happening right now and the other will not happen for a very long time.

So if you want to make money in the AI boom, you have to invest with one of these types of AI… and forget about the other type.

As you probably guessed, the type of AI that is happening right now is narrow or specific AI. Specific AI involves taking an AI algorithm and training it to do a very particularly defined task, a narrowly defined task or a specific task. The simplest version of this actually, believe it or not, are the iRobot vacuums – the Roombas or the Shark vacuums, the Shark Ninja vacuum.

So, you know, those little vacuums are like little circular things, and they go around your house and they clean, and they’re not very good. But that is the simplest form of specific AI because there is AI in those things where it’s mapping out and learning your house, and trying to get better at vacuuming your house and keeping it cleaner, especially the newer versions.

But that’s narrow AI because it’s very much defined: You [the vacuum] clean the floors, you don’t do other things, you clean the floors, you don’t also mop, you don’t also go and clean the windows, you don’t grow arms and wipe the counters. You vacuum the floors.

That’s narrow and specific AI. Narrow and specific AI is being broadly used today across a variety of applications well beyond and way more advanced than those silly little iRobot vacuums. But the other type of AI, general AI, is not being widely deployed yet.

General AI involves taking an AI, giving it a bunch of data, training it on that data and giving it the task of not just making predictions and doing things within that data set, but then expanding beyond that data set and doing things beyond what it is trained on. That’s where like real complex reasoning for humans comes into play, right?

Because a human can learn about basketball and then take some of the learnings it had about basketball and apply it to football. Some of the cuts might be similar, some of the plays might be similar, some of the camaraderie, the energy and the teamwork might be similar.

That’s what general AI should be able to do, but AI is not there yet.

The development of AI today is really focused on narrow AI, it’s really good at learning basketball and making predictions about basketball. But if you tell that basketball-trained AI to do something in football, and it is going to fail 99 times out of 100.

One of my good friends is actually studying AI at one of the world’s leading AI research labs at MIT. He is getting his Ph.D. in artificial intelligence and robotics, and he and I had a very in-depth conversation about the differences between narrow and general AI.

He told me something that I have always remembered: They are 10 to 20 years apart in terms of development. Narrow AI can and will happen right now. General AI will not happen until at least the 2030s – if not later. And that’s because the fundamental building blocks of them actually aren’t the same; the algorithms you’re using to train narrow AI cannot be used to train general AI.

They’re different, they’re distinct.

So we have to know that difference as AI investors, if you want to make money in this boom. Somebody might come in with a general AI and say it’s going to work. It’s not. You have to ignore that and focus on the narrow, specific AI programs out there that are killing it at a very specific task and doing very well at that one thing.

Invest in the AI specialist, as I like to say, not the AI generalist.

So those are the two very different types of AI that are emerging in the world right now: specific, narrow AI and general AI.

Now the one thing that we want to talk about then, of course, is I told you narrow and specific AI is being used across the world right now… where? Where is this AI being used?

What I told you about the Irobot vacuums – okay, that’s cool. But there’s also a lot of other robotic automation going on.

So, I have another friend that I graduated with, that I actually played college basketball with, and he went on to co-found a company called Miso Robotics.

Now, Miso Robotics is based in Pasadena, California. They raised a whole bunch of money, and they’ve been very successful. Their first product was an AI-powered, burger-flipping robot called “Flippy.”

So, it’s a robot that goes into fast food kitchens and learns how to flip burgers and flips those burgers very, very well and does it very, very efficiently. And that was their hero product.

They’ve since created “Sippy” and “Chippy” and all these other products that make chips, make sodas, do all these different things, and it’s all based on the same core AI algorithm of: Get this robot to be very good at doing this one thing: flipping burgers, making chips, making sodas, whatever it may be.

They’ve won deals with White Castle. The biggest deal is a deal with Jack-In-The-Box. They’re expanding; it’s a big company. They’re growing very, very nicely. My friend is very, very happy with the success they’ve had.

But that is an example of narrow AI in the real world today that’s actually happening.

You go to some restaurants in California, specifically in Los Angeles, they have the Flippy; they have these robots doing work in the kitchens. And they’re not alone; there’s a lot of other restaurant automation happening.

Chili’s is using robotic servers, a very interesting application of AI. There are sushi bars that are using robotic servers and robotic sushi constructions as well. So, that’s another interesting application of narrow AI in the world right now.

Beyond the world of restaurants, still in the robotics field, there is major warehouse automation happening. I have another friend who started a warehouse automation startup, raised a bunch of money there, and the whole idea is that they create little robots and little machines and AI to automate the processes in a warehouse.

If you think about a warehouse, the processes are pretty repetitive and monotonous – it’s the same thing over and over again. Stock, taking inbound parcels, taking them apart, stocking that stuff in the warehouse, going and retrieving that stuff, creating inbound parcels, putting it on the truck and saying, go off to the local store…

That’s a very repetitive, monotonous process. So when you have repetition and monotony, you have a foundation upon which you can build really good AI programs – which AI is very capable of tackling today. So, you’re getting a lot of warehouse automation going on right now.

There’s a company, one of my favorites out there, called Symbotic (SYM), that is automating all of the warehouses for Walmart right now. That stock’s been on fire this year – absolute fire-starter.

So, there is big success happening in that field as well. So, the whole automation thing, warehouse automation, restaurant automation, retail automation… you’re seeing it. You’ve got the self-checkout kiosk – that’s not AI, but retailers are starting to use AI to stock shelves, to clean aisles, to do things like that. Some are using them for self-help as well.

So, there are a lot of cool things happening in the automation world.

Another big application of AI, as I mentioned or hinted earlier, is self-driving.

Self-driving cars are actually becoming a thing now because of AI. I was just in San Francisco two days ago, and I was sitting there on a street corner, on my phone talking to somebody, look over and there’s a Waymo car – Waymo is the self-driving unit of Google – and Waymo has self-driving, ride-sharing operations live in San Francisco.

And when I mean, self-driving, ride-sharing operations, I mean they have cars without any person in it, no human at all, driving around the street, and then they go and pick somebody up to sit in the back.

It’s through their Waymo One app. Download the app and you can hail a ride from Waymo, the car will drive itself to you, pick you up, you get in it, and it takes you to where you want to go. Those are live.

So I’m sitting there on my phone, and I look over, and there’s a Waymo car. I peer around, try to look through the side window, the front window – nobody! And then it just stops at a red light, waits, turns the corner, goes off and zooms off down a couple of streets, and I lose sight of it, but there it was in action. Five minutes later, I saw another one. 10 minutes later, I saw another one. They’re all over. So self-driving is now becoming a real thing.

Some of you probably own Teslas, and you know, firsthand, the self-driving experience. AI is making self-driving cars a real reality right now. You’re seeing fully autonomous, no person in them, ride-sharing operations live in San Francisco, Phoenix, Arizona, coming to Las Vegas, coming to San Diego, Los Angeles, Austin, Texas… You’re seeing this spread pretty rapidly, and that’s just in America. Off in China, they’re having a lot of tests in Beijing, Shanghai, et cetera, et cetera.

This is a real movement. Yes, I know we’ve been promised self-driving cars for a long time now, but this is a real movement that is finally starting, thanks to artificial intelligence. That’s another big application.

Now, another big application of AI, which I know Eric Fry is really excited about himself – because we talk about it all the time – is energy-plus-AI.

In the world of energy, there’s a lot of data, usable, important, and valuable data.

• How much energy does your home use…
• At what time does it use at peak loads, off hours…
• The pricing of that data, renewable mix, solar panel efficiency, wind turbine efficiency, non-renewable mix…

There’s a lot of really good data in the energy industry.

AI can go in there with machine-learning algorithms, run the loop, get trained on that data, run and get really smart at how to optimize our grid and make predictions about…

• This office is going to need energy at 4 p.m.…
• They’re going to need it at 6 p.m.…
• They’ve got the peak over here at 2:30 p.m.…
• We can use solar over here because we are going to get a lot of sun in about two or three days…
• We’re going to get a lot of wind over here…

And it can kind of take all that and create this web, this interconnected web of optimized energy deployment and usage. In the future, AI-plus-energy can create a very strong, reliable grid, not to mention, AI can also help us get to a place where I believe there will be limitless energy.

Follow me here, I know this might seem like a bold claim, limitless energy, but ChatGPT – the chatbot that is taking over the world, was created by Open AI. Open AI’s founder is a gentleman named Sam Altman. Sam Altman has taken all of his AI money and plowed it into a nuclear fusion startup called Helion. He has invested $375 million into a tiny firm called Helion; Helion is a nuclear fusion startup.

So quick science lesson: There’s fission and fusion. Fission is the tearing apart of atoms; fusion is the combining of atoms.

Fission, when you tear stuff apart, unstable nuclei – that’s when you get the boom, radioactive waste.

And fusion – none of that. No unstable nuclei, no radioactive waste. It’s perfectly safe… It’s just nearly impossible to do. And no one’s really figured out how to do it – it’s what powers the sun.

It’s the most powerful thing you can imagine. But no one’s really been able to figure out what the sun does naturally, how to replicate that on Earth. That’s nuclear fusion.

But with AI, we’re starting to put together that mystery, solve that mystery. Sam Altman – the guy who was the pioneer of the AI revolution, the godfather of it, if you will, the one who started this whole thing – he’s putting his money where his mouth is.

He’s saying, You know what? AI is going to allow us to do nuclear fusion. It’s going to create limitless energy. I’m taking all the money I’m making from my AI startup and putting into this nuclear fusion startup, because that is the real future.

So that’s where I get really excited. I think that energy-plus-AI, good optimization – very cool, very valuable, very economically useful, but… AI-plus-nuclear fusion, limitless energy, solves the world’s entire energy problems forever.

Sam Altman – ChatGPT’s creator and Open AI founder – believes it, $375 million worth believes it. So I believe it too; I think the science is there to support that.

So that’s really exciting and that’s a really exciting application of AI happening right now.

Now we’re talking about AI right now. We have to think, OK, a lot of things going on. Obviously, you’ve got the chatbots, there’s awesome design things going on, asset-pricing companies like Opendoor using AI to price homes. Rocket Mortgage, obviously using them to price mortgages, Goldman Sachs, JPMorgan, Bank of America, use these to price bonds and other financial assets. So that makes a ton of sense.

When you think about all these applications of AI, if you want to be a really successful AI investor, you have to be able to find the best of the best.

What are the biggest impacts of AI and in which industries are you going to see the biggest impacts?

In my personal opinion, I think the biggest impacts are going to happen in robotics, medicine, and energy.

We’ve talked about energy – I think the nuclear fusion thing is, wow. We’ve talked about robotics; I think the automation of warehouses, the automation of transportation, the automation of restaurants, the automation of retail… it’s going to be huge.

And another part here is medicine.

When you think about the human body, we’re really just a bunch of data. We have our genetic data, we have our immunogenic data, we have a whole bunch of different data. You know, our cholesterol, our blood levels, blood types… all these different things. We really are just a bunch of data, like a computer is just a bunch of data.

We figured out how to use AI to optimize software systems to make them automated, to make them efficient, to make them better than ever. We can use AI to make the human body optimized, to make it faster, more efficient and better than ever.

And that is what a lot of companies are working on right now. There are a whole host of startups out there, biotech startups, that are leveraging AI to come into the human body, map out the genetic, immune system and all the data of an individual, take that data and understand how to prevent diseases, how to cure diseases, how to delay aging… all that stuff.

They say that the world’s first 150-year-old is already born. I 100% believe that. I’m a father of two. I have a three-year-old daughter and a seven-month-old boy.

I think they and their peers both have a good shot of living to 150, if not older, because the advancements in AI are truly going to unlock the mystery of the human body. And like we’ve made optimized machines, we can make optimized humans.

I’m not talking about Androids, cyborgs or all that weird science-fiction stuff. No, I’m just talking about taking the human body and making it as good as it can be – elongating the health of the human body. I think longevity is going to be a huge thing.

I think that’s going to be a massive application of artificial intelligence over the next five to 10 years.

So, you put all that together: robotics, medicine, and energy. Those, in my opinion, are the “big three” of AI, in terms of AI investing, where we as AI investors, from the outside looking in, can make the most money, find the best companies in those three areas, and I think you have a chance at hitting some grand-slam victories.

Now beyond those big three, how is AI going to impact society, the economy, and the financial markets?

Because as you may have noticed, we have had a stock market boom here in 2023. AI stocks have led the way, but it’s been the whole market that’s rallying too. So, it’s not just like AI is rallying and everything else is being left behind; AI is rallying a lot more than everything else, but all stocks are catching a bid and everything’s moving higher.

Why is AI doing that? Why is AI providing a driver for the entire economy?

Because of improved productivity. When we talk about improved productivity, we’re talking about bigger profit margins.

Two fun facts.

1. As go stocks, so go earnings.

Pull up a chart of the S&P 500, pull up a chart of its earnings over the past 30 to 40 years. The two go hand in hand: When earnings go up, stocks go up, and when earnings go down, stocks go down. They’re tied together, and they will forever be tied together. They are joined at the hip. That’s fun fact number one.

2. Look at sales in the S&P 500.

You get all the S&P 500 companies, tally up all their sales. Sales over the past 30 years are up about 250%. Earnings? Tally up all the earnings; earnings are up 1,300%.

So how do you turn 250% sales growth into 1,300% earnings growth?

Through profit margin expansion.

Back in the early ‘90s, S&P 500 companies averaged a profit margin of about 2%. Today? 10%. We have 5X’d the profit margins of companies in America, allowing 260% sales growth to turn into 1,300% earnings growth.

And stocks don’t follow sales, they follow earnings. So if earnings are 1,300%, then stocks follow suit with that bigger return and leave the sales return in the dust. Profit margin expansion, not sales growth, has been the big driver of stocks over the past 40 years.

And why is that?

Because the internet unlocked human productivity like never before. We were able to automate things, do things remotely and do things more quickly and efficiently than we ever thought was possible.

So costs came down, gross margins went up, and profit margins for these companies went up. And that’s how you went from 2% profit margins to 10% profit margins because of the internet unlocking productivity.

Lather, rinse, repeat with AI. AI is going to unlock productivity too, a whole bunch of productivity – more productivity than the internet ever unlocked.

So we’re going to go from, in my opinion, 10% profit margins today, to 20-to-25% profit margins in the next 10 to 15 years.

That’s going to turn probably 100%-to-150% sales growth into 500%, 600%, and 700% earnings growth. You’re going to get an earnings growth supercharge over the next 10 to 15 years, which is going to cause stocks to go higher because stocks and earnings are tied at the hip.

It’s improved productivity and bigger profit margins, that’s the real big economic and financial market impact of AI. And that’s why AI is a driver for the entire economy and the entire stock market. It’s a win for everyone in that regard.

So, of course, having said all that, you know, what are some of the best AI stocks to buy today?

Well, Eric’s already given you a bunch of really great ones. I want to piggyback on his pick of Stem; I think Stem is a fantastic stock.

I think that there are a lot of stocks out there that are doing really well at the current moment in energy and AI.

Another personal favorite of mine is a company called Fluence – FLNC is the ticker. They’re using energy and AI to optimize grid systems around energy storage systems. So I think that’s a really interesting application.

We talked about Symbotic earlier in this conversation – ticker symbol SYM – that stock has been a huge winner, got the contract with Walmart. They’re automating all those warehouses. I think that’s a very, very interesting pick.

And then the more under-the-radar one for you is a company called Recursion – RXRX is the ticker. They’re working with NVIDIA for drug discovery, using AI for drug discovery. It’s a fantastic firm. Really, really smart people over there. Pre-revenue, early-stage, definitely a high-risk company, but the potential reward is there.

I mean, when we talk about potential grand-slam hits, I think Recursion, Symbotic, and Fluence kind of have that potential. So, really excited about those three stocks.

Now, I want to thank you for your time today, but I also want to conclude by talking about one final thing. You know, everyone thinks about getting rich in AI, investing in the right AI stocks, that’s true. But what about using AI to become better stock pickers ourselves?

As I said earlier, every day, the stock market produces a ton of data. The economy produces a ton of data. The bond market produces a ton, the crypto markets… Every day, the financial and economic landscapes produce a ton of data.

What is required for a good AI model? A ton of data, a ton of high-quality, continuous time series data.

You give that to a machine-learning algorithm, and boom, you can create, if your machine-learning algorithm is any good, you can create some really fantastic and capable AI.

So I think a really slept-on part of the AI boom, and getting rich in the AI boom, is using AI to pick stocks, or to pick bonds, or to pick crypto, or to pick your poison.

Whatever you like to invest in, there is a way to use AI to improve your investing strategy in that area, and that’s something that I’m really excited about. And I’m really thinking about a lot right now, and saying, “Okay, this is, this is my world, Eric’s world, we’re stock pickers, we pick stocks. How can we use AI to get better at our jobs? How can we use AI as our tool, our ultimate weapon, differentiator, to become better stock pickers than everybody else hopefully?”

So, that’s something my wheels are turning about that. I think about this when I put my head on the pillow every night. How can we use AI to become better at what we do?

Because AI is going to transform the world, people who figure out how to use AI in their careers are going to get ahead of those who don’t. So, I’m thinking about it in my career and I would highly encourage anybody that’s still working and has a career, in one way or another, to think about how can you use AI to improve what you’re doing on a daily basis to improve my efficiency, to reduce my cost, to accelerate my time, to produce better outcomes for my customers… how can I do that?

So that’s something I’m thinking about – something I think everyone else should be thinking about.

Anyway, I want to thank you for your time. That’s about all the time I have today, about 30 minutes. I promised, Eric, I’d keep it under 30 – we’re a little bit over 30 here right now.

But I want to thank you for your time. I hope you enjoyed this video. Again, Eric just entrusted me with doing this because artificial intelligence; it’s what I live and breathe. This is my game; I play basketball and I do AI – that’s kind of what I’m known for, this is my wheelhouse.

So, I just wanted to come in here and give you all the AI knowledge I could in 30 minutes. Distill all that information to you in a way that’s very understandable, tangible, and in a way that you can take and actually create action from and make money from this AI boom.

That’s what we want to do at the end of the day, right? We want to make money from this AI boom. We don’t just want to learn about it and know about it; we want to do those things so that we can make money off it, profit off this revolution. And I hope today puts you – or at least gives you a couple of tools – to get down that path of making money from the AI boom.

Well, folks, that’s all I have for this video. I want to thank you again for your time. Signing off, this is Luke Lango.